Triple
T35094528
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marquise de San-Réal |
E1012829
|
entity |
| Predicate | deathCaused |
P29920
|
FINISHED |
| Object | Paquita Valdès |
—
|
NE NERFINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Paquita Valdès | Statement: [Marquise de San-Réal, deathCaused, Paquita Valdès]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: deathCaused Context triple: [Marquise de San-Réal, deathCaused, Paquita Valdès]
-
A.
deathResultedIn
Indicates that one event, action, or condition caused or led directly to a particular death as its outcome.
-
B.
deathOutcome
Indicates that an event, condition, or action results in the death of the affected entity.
-
C.
deathCharacteristic
Indicates a characteristic, attribute, or quality specifically associated with a death event or the manner in which death occurred.
-
D.
causeOfDeath
Indicates the specific factor, event, or condition that directly resulted in an entity’s death.
-
E.
deathContributedTo
chosen
Indicates that one entity played a causal or contributing role in bringing about the death of another entity.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69f76dd432ec8190969bc32acfc152b1 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69f7979a073881909a4fde2558e6b6f3 |
completed | May 3, 2026, 6:44 p.m. |
| PD | Predicate disambiguation | batch_69f7961550f88190b7bb8a9155458b54 |
completed | May 3, 2026, 6:38 p.m. |
Created at: May 3, 2026, 4:01 p.m.